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Synthetic Data Generation Jobs (NOW HIRING)

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Platform Engineer, Data

Austin, TX

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Platform Engineer, Data

Austin, TX

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

... synthetic data generation, ensuring seamless integration with machine learning training loops (e.g., Reinforcement Learning, Computer Vision). • Proactively identify and mitigate risks, failure ...

Develop synthetic data generation workflows, including scenario and agent behavior generation, to support model training * Work closely with ML and autonomy engineers to measure and reduce sim-to ...

Informatica Admin

Newark, NJ

$55.50 - $73/hr

Synthetic data generation PII anonymization Data privacy compliance Build pipelines between Informatica, databases, and Tonic AI. Automate masking and synthetic data workflows using TDM + Tonic AI.

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Synthetic Data Generation information

See salary details

$31K

$93.2K

$169K

How much do synthetic data generation jobs pay per year?

As of Jun 9, 2026, the average yearly pay for synthetic data generation in the United States is $93,198.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,500.00 and $144,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in a Synthetic Data Generation role, and why are they important?

To excel in a Synthetic Data Generation role, you need a solid background in computer science, statistics, and data science, often supported by a relevant degree and experience in machine learning. Familiarity with tools such as Python, TensorFlow, PyTorch, and synthetic data generation platforms, as well as knowledge of privacy-preserving techniques, is typically required. Strong problem-solving abilities, creativity, and effective communication set top performers apart in this field. These skills and qualities are crucial for creating high-quality, realistic synthetic datasets that support robust AI model development while safeguarding sensitive information.

What is synthetic data generation?

Synthetic data generation is the process of creating artificial datasets that mimic real-world data. This technique is used to supplement or replace actual data for purposes such as machine learning, software testing, and research, especially when real data is scarce, sensitive, or costly to obtain. Synthetic data can help improve model accuracy, protect privacy, and enable innovation by providing diverse and unbiased datasets. It is commonly used in fields like healthcare, finance, and autonomous vehicles.

What is the difference between Synthetic Data Generation vs Data Analyst?

AspectSynthetic Data GenerationData Analyst
Required CredentialsKnowledge of data science, programming, and data privacyDegree in statistics, data science, or related field
Work EnvironmentData science teams, research labs, tech companiesBusiness environments, analytics teams, consulting firms
Industry UsageAI development, machine learning, data privacyBusiness insights, reporting, decision-making
Search & Comparison IntentUnderstanding data generation techniques, privacy solutionsAnalyzing data, generating reports, insights

While Synthetic Data Generation focuses on creating artificial data for privacy and model training, Data Analysts interpret existing data to provide business insights. Both roles require data-related skills but serve different purposes within the data ecosystem.

What are the main challenges faced by professionals working in synthetic data generation, and how can they be addressed?

Professionals in synthetic data generation often encounter challenges such as ensuring the generated data accurately represents real-world scenarios while maintaining privacy and data security. Balancing realism with anonymization is crucial, especially when synthetic data is used for AI model training or testing. Collaboration with data scientists, domain experts, and privacy officers is common to validate data utility and compliance with regulations. Staying current with advances in generative models and data validation techniques also helps address these challenges and contributes to career growth in this rapidly evolving field.
More about Synthetic Data Generation jobs
What cities are hiring for Synthetic Data Generation jobs? Cities with the most Synthetic Data Generation job openings:
What states have the most Synthetic Data Generation jobs? States with the most job openings for Synthetic Data Generation jobs include:
Infographic showing various Synthetic Data Generation job openings in the United States as of May 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 60% In-person, 15% Hybrid, and 25% Remote job distribution, with an average salary of $93,198 per year, or $44.8 per hour.

Isaac Sim Expert / Simulation Engineer

ConfigUSA

Mountain View, CA • On-site

Contractor

Posted 20 days ago


Job description

Simulation Engineer

Pre-Screening Questionnaire:

-Have you worked on an Isaac Sim project?

-Do you have exposure to simulation projects?

Must Have Technical/Functional Skills:

Proficiency in NVIDIA Isaac Sim, Omniverse, and synthetic data generation tools Strong understanding of CAD model handling and 3D asset integration Experience with Python, C++, and simulation scripting Familiarity with ROS/ROS2, Gazebo, Unity, or other simulation platforms is a plus Knowledge of computer vision and deep learning frameworks (PyTorch, TensorFlow, OpenCV) Prior experience in auto-labeling pipelines and dataset generation for AI models Publications, patents, or projects in simulation-based robotics development are a plus

Roles & Responsibilities:

Develop and maintain simulation environments using NVIDIA Isaac Sim and Omniverse Integrate CAD models and create synthetic datasets for training computer vision models Implement auto-annotation pipelines for object detection, segmentation, and tracking Simulate multi-sensor setups (camera, LiDAR, radar, depth sensors) for perception validation Support testing of vision-based algorithms in virtual environments before real-world deployment Collaborate with AI and robotics teams to simulate robotic tasks like pick-and-place, navigation, and human-robot interaction Optimize simulation performance and realism for accurate model training and testing

Generic Managerial Skills, If any:

The engineer will work closely with AI researchers and robotics engineers to simulate real-world scenarios and optimize perception systems..

Key Words to search in Resume:

Isaac Sim Expert, Simulation Engineer, Synthetic Data Generation, CAD Integration, Robotics Simulation, Omniverse, Auto-Annotation, Multi-Sensor Simulation, AI for Robotics

Education:

 Master’s/bachelor’s in computer science, AI, Robotics, or related field